Abstract
Super-resolution (SR) reconstruction technique is capable of producing a high-resolution image from a sequence of low-resolution images. In this paper, we study an efficient SR algorithm for digital video. To effectively deal with the intractable problems in SR video reconstruction, such as inevitable motion estimation errors, noise, blurring, missing regions, and compression artifacts, the total variation (TV) regularization is employed in the reconstruction model. We use the fixed-point iteration method and preconditioning techniques to efficiently solve the associated nonlinear Euler-Lagrange equations of the corresponding variational problem in SR. The proposed algorithm has been tested in several cases of motion and degradation. It is also compared with the Laplacian regularization-based SR algorithm and other TV-based SR algorithms. Experimental results are presented to illustrate the effectiveness of the proposed algorithm.
Highlights
Solid-state sensors such as CCD or CMOS are widely used nowadays in many image acquisition systems
This method would lead to a small signal-to-noise ratio (SNR) because the amount of photons collected in each photodetector decreases correspondingly
It is noted that the Laplacian regularization generally has stronger constraint on the image than the total variation (TV) regularization because it is a square term and not extracted like the TV regularization, so it should require a smaller regularization parameter
Summary
Solid-state sensors such as CCD or CMOS are widely used nowadays in many image acquisition systems. Such sensors consist of rectangular arrays of photodetectors where their physical sizes limit the spatial resolution of acquired images. In order to increase the spatial resolution of images, one possibility is to reduce the size of rectangular array elements by using advanced sensor fabrication techniques. This method would lead to a small signal-to-noise ratio (SNR) because the amount of photons collected in each photodetector decreases correspondingly. In order to get a more desirable high-resolution (HR) images, superresolution (SR) technique can be employed as an effective and efficient alternative
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